Netflix/void-model
File Size
The distribution of size of files (measured in lines of code).
File Size Overall
  • There are 68 files with 21,430 lines of code.
    • 4 very long files (5,714 lines of code)
    • 8 long files (5,326 lines of code)
    • 23 medium size files (7,710 lines of code)
    • 14 small files (1,960 lines of code)
    • 19 very small files (720 lines of code)
26% | 24% | 35% | 9% | 3%
Legend:
1001+
501-1000
201-500
101-200
1-100


explore: grouped by folders | grouped by size | sunburst | 3D view
File Size per Extension
1001+
501-1000
201-500
101-200
1-100
py27% | 25% | 34% | 9% | 3%
ipynb0% | 0% | 100% | 0% | 0%
File Size per Logical Decomposition
primary
1001+
501-1000
201-500
101-200
1-100
scripts100% | 0% | 0% | 0% | 0%
data_generation32% | 0% | 36% | 27% | 3%
videox_fun11% | 49% | 28% | 6% | 3%
VLM-MASK-REASONER0% | 17% | 78% | 4% | 0%
inference0% | 0% | 94% | 0% | 6%
ROOT0% | 0% | 100% | 0% | 0%
config0% | 0% | 0% | 0% | 100%
Longest Files (Top 50)
File# lines# units
train_warped_noise.py
in scripts/cogvideox_fun
 1678 7
train.py
in scripts/cogvideox_fun
 1557 7
1386 32
cogvideox_vae.py
in videox_fun/models
 1093 45
877 26
dataset_image_video.py
in videox_fun/data
 858 26
pipeline_cogvideox_fun_inpaint.py
in videox_fun/pipeline
 856 24
cogvideox_transformer3d.py
in videox_fun/models
 570 15
cogvideox_fun_ui.py
in videox_fun/ui
 557 5
edit_quadmask.py
in VLM-MASK-REASONER
 540 31
wan_fun_ui.py
in videox_fun/ui
 535 5
pipeline_cogvideox_fun.py
in videox_fun/pipeline
 533 19
utils.py
in videox_fun/utils
 497 17
kubric_variable_objects.py
in data_generation
 477 6
stage2_vlm_analysis.py
in VLM-MASK-REASONER
 454 12
stage2_vlm_analysis_cf.py
in VLM-MASK-REASONER
 450 12
lora_utils.py
in videox_fun/utils
 401 18
point_selector_gui.py
in VLM-MASK-REASONER
 393 29
optical_flow_utils.py
in videox_fun/utils
 388 13
pipeline_wan_fun.py
in videox_fun/pipeline
 387 13
blender_utils.py
in data_generation
 374 12
345 13
339 -
object_texture_mapping.py
in data_generation
 316 6
bucket_sampler.py
in videox_fun/data
 302 12
inference_with_pass1_warped_noise.py
in inference/cogvideox_fun
 298 4
reward_fn.py
in videox_fun/reward
 296 11
stage3a_generate_grey_masks.py
in VLM-MASK-REASONER
 289 11
stage3b_trajectory_gui.py
in VLM-MASK-REASONER
 288 15
stage1_sam2_segmentation.py
in VLM-MASK-REASONER
 276 6
predict_v2v.py
in inference/cogvideox_fun
 266 3
ui.py
in videox_fun/ui
 232 14
dataset_video.py
in videox_fun/data
 219 11
213 8
human_model.py
in data_generation/human_model
 210 11
api_multi_nodes.py
in videox_fun/api
 191 4
api.py
in videox_fun/api
 180 9
physics_review_ui.py
in data_generation
 180 4
166 7
cross_modeling.py
in videox_fun/reward/MPS/trainer/models
 152 18
145 6
stage4_combine_masks.py
in VLM-MASK-REASONER
 139 4
blender_helper.py
in data_generation/scripts
 130 8
transfer_human_model.py
in data_generation/scripts
 127 3
123 3
clear_human_scale.py
in data_generation/scripts
 110 1
siglip_v2_5.py
in videox_fun/reward/aesthetic_predictor_v2_5
 107 8
extract_pk_data.py
in data_generation/scripts
 107 3
generate_review_frames.py
in data_generation
 103 3
clip_model.py
in videox_fun/reward/MPS/trainer/models
 94 9
Large Files That Change Often (Top 20)
To change a file, an AI coding agent (or a person) has to read it: these files are read the most for the changes in the past year (lines × changes).
File# lines≈ tokens
to read		# changes
(1y)		≈ lines edited
per change		lines read per
line changed
1386 ~7k–20k 2 ~1,000 ~1
339 ~2k–5k 3 ~100 ~3
kubric_variable_objects.py
in data_generation
 477 ~3k–7k 1 ~700 ~1
blender_utils.py
in data_generation
 374 ~2k–7k 1 ~700 ~1
object_texture_mapping.py
in data_generation
 316 ~2k–5k 1 ~500 ~1
inference_with_pass1_warped_noise.py
in inference/cogvideox_fun
 298 ~2k–5k 1 ~500 ~1
predict_v2v.py
in inference/cogvideox_fun
 266 ~1.5k–5k 1 ~300 ~1
213 ~1k–3k 1 ~300 ~1
human_model.py
in data_generation/human_model
 210 ~1k–3k 1 ~300 ~1
physics_review_ui.py
in data_generation
 180 ~1k–3k 1 ~300 ~1
166 ~1k–3k 1 ~300 ~1
145 ~1k–3k 1 ~200 ~1
blender_helper.py
in data_generation/scripts
 130 ~700–2k 1 ~200 ~1
transfer_human_model.py
in data_generation/scripts
 127 ~700–2k 1 ~200 ~1
123 ~700–2k 1 ~200 ~1
clear_human_scale.py
in data_generation/scripts
 110 ~700–2k 1 ~200 ~1
extract_pk_data.py
in data_generation/scripts
 107 ~700–1.5k 1 ~150 ~1
generate_review_frames.py
in data_generation
 103 ~700–1.5k 1 ~300 ~0
generate_physics_config.py
in data_generation
 82 ~500–1.5k 1 ~100 ~1
76 ~500–1.5k 1 ~100 ~1

Tokens are lines × 7 to 14 (analysis.fileReadsForChanges). Lines edited per change are the file's lines added and deleted divided by its commits over the whole history. Agents read about 2,000 lines at a time: when a 17,000-line file was split into modules, the tokens an agent read for the same change fell by 83% (The Economic Benefit of Refactoring, 2026).

Files With Most Units (Top 50)
File# lines# units
cogvideox_vae.py
in videox_fun/models
 1093 45
1386 32
edit_quadmask.py
in VLM-MASK-REASONER
 540 31
point_selector_gui.py
in VLM-MASK-REASONER
 393 29
877 26
dataset_image_video.py
in videox_fun/data
 858 26
pipeline_cogvideox_fun_inpaint.py
in videox_fun/pipeline
 856 24
pipeline_cogvideox_fun.py
in videox_fun/pipeline
 533 19
lora_utils.py
in videox_fun/utils
 401 18
cross_modeling.py
in videox_fun/reward/MPS/trainer/models
 152 18
utils.py
in videox_fun/utils
 497 17
stage3b_trajectory_gui.py
in VLM-MASK-REASONER
 288 15
cogvideox_transformer3d.py
in videox_fun/models
 570 15
ui.py
in videox_fun/ui
 232 14
345 13
pipeline_wan_fun.py
in videox_fun/pipeline
 387 13
optical_flow_utils.py
in videox_fun/utils
 388 13
stage2_vlm_analysis_cf.py
in VLM-MASK-REASONER
 450 12
stage2_vlm_analysis.py
in VLM-MASK-REASONER
 454 12
bucket_sampler.py
in videox_fun/data
 302 12
blender_utils.py
in data_generation
 374 12
stage3a_generate_grey_masks.py
in VLM-MASK-REASONER
 289 11
reward_fn.py
in videox_fun/reward
 296 11
dataset_video.py
in videox_fun/data
 219 11
human_model.py
in data_generation/human_model
 210 11
clip_model.py
in videox_fun/reward/MPS/trainer/models
 94 9
api.py
in videox_fun/api
 180 9
siglip_v2_5.py
in videox_fun/reward/aesthetic_predictor_v2_5
 107 8
blender_helper.py
in data_generation/scripts
 130 8
213 8
train_warped_noise.py
in scripts/cogvideox_fun
 1678 7
train.py
in scripts/cogvideox_fun
 1557 7
166 7
stage1_sam2_segmentation.py
in VLM-MASK-REASONER
 276 6
object_texture_mapping.py
in data_generation
 316 6
kubric_variable_objects.py
in data_generation
 477 6
145 6
76 5
58 5
58 5
wan_fun_ui.py
in videox_fun/ui
 535 5
cogvideox_fun_ui.py
in videox_fun/ui
 557 5
stage4_combine_masks.py
in VLM-MASK-REASONER
 139 4
fp8_optimization.py
in videox_fun/utils
 47 4
cache_utils.py
in videox_fun/models
 57 4
38 4
api_multi_nodes.py
in videox_fun/api
 191 4
dataset_image.py
in videox_fun/data
 62 4
inference_with_pass1_warped_noise.py
in inference/cogvideox_fun
 298 4
physics_review_ui.py
in data_generation
 180 4
Files With Long Lines (Top 39)

There are 39 files with lines longer than 120 characters. In total, there are 362 long lines.

File# lines# units# long lines
train_warped_noise.py
in scripts/cogvideox_fun
 1678 7 53
train.py
in scripts/cogvideox_fun
 1557 7 47
cogvideox_fun_ui.py
in videox_fun/ui
 557 5 38
wan_fun_ui.py
in videox_fun/ui
 535 5 37
ui.py
in videox_fun/ui
 232 14 24
877 26 17
cogvideox_transformer3d.py
in videox_fun/models
 570 15 15
dataset_image_video.py
in videox_fun/data
 858 26 15
pipeline_cogvideox_fun_inpaint.py
in videox_fun/pipeline
 856 24 14
1386 32 14
utils.py
in videox_fun/utils
 497 17 9
339 - 7
human_model.py
in data_generation/human_model
 210 11 7
stage3b_trajectory_gui.py
in VLM-MASK-REASONER
 288 15 6
lora_utils.py
in videox_fun/utils
 401 18 5
api_multi_nodes.py
in videox_fun/api
 191 4 5
predict_v2v.py
in inference/cogvideox_fun
 266 3 5
clear_human_scale.py
in data_generation/scripts
 110 1 5
edit_quadmask.py
in VLM-MASK-REASONER
 540 31 4
pipeline_wan_fun.py
in videox_fun/pipeline
 387 13 4
reward_fn.py
in videox_fun/reward
 296 11 4
166 7 4
point_selector_gui.py
in VLM-MASK-REASONER
 393 29 3
stage2_vlm_analysis_cf.py
in VLM-MASK-REASONER
 450 12 2
stage2_vlm_analysis.py
in VLM-MASK-REASONER
 454 12 2
api.py
in videox_fun/api
 180 9 2
transfer_human_model.py
in data_generation/scripts
 127 3 2
58 5 1
58 5 1
pipeline_cogvideox_fun.py
in videox_fun/pipeline
 533 19 1
38 4 1
dataset_video.py
in videox_fun/data
 219 11 1
bucket_sampler.py
in videox_fun/data
 302 12 1
make_warped_noise.py
in inference/cogvideox_fun
 36 1 1
inference_with_pass1_warped_noise.py
in inference/cogvideox_fun
 298 4 1
blender_utils.py
in data_generation
 374 12 1
object_texture_mapping.py
in data_generation
 316 6 1
kubric_variable_objects.py
in data_generation
 477 6 1
extract_pk_data.py
in data_generation/scripts
 107 3 1
Correlations

File Size vs. Commits (all time): 25 points

notebook.ipynb x: 3 commits (all time) y: 339 lines of code inference/cogvideox_fun/inference_with_pass1_warped_noise.py x: 1 commits (all time) y: 298 lines of code inference/cogvideox_fun/make_warped_noise.py x: 1 commits (all time) y: 36 lines of code inference/cogvideox_fun/predict_v2v.py x: 1 commits (all time) y: 266 lines of code data_generation/render_paired_videos_blender_quadmask.py x: 2 commits (all time) y: 1386 lines of code data_generation/human_model/human_model.py x: 1 commits (all time) y: 210 lines of code data_generation/human_model/__init__.py x: 1 commits (all time) y: 1 lines of code data_generation/apply_physics_config.py x: 1 commits (all time) y: 49 lines of code data_generation/blender_utils.py x: 1 commits (all time) y: 374 lines of code data_generation/convert_all_scenarios_for_characters.py x: 1 commits (all time) y: 145 lines of code data_generation/convert_masks_to_grid_hybrid.py x: 1 commits (all time) y: 213 lines of code data_generation/convert_trimask_to_quadmask.py x: 1 commits (all time) y: 166 lines of code data_generation/generate_physics_config.py x: 1 commits (all time) y: 82 lines of code data_generation/generate_review_frames.py x: 1 commits (all time) y: 103 lines of code data_generation/generate_review_frames_direct.py x: 1 commits (all time) y: 123 lines of code data_generation/kubric_variable_objects.py x: 1 commits (all time) y: 477 lines of code data_generation/object_texture_mapping.py x: 1 commits (all time) y: 316 lines of code data_generation/physics_review_ui.py x: 1 commits (all time) y: 180 lines of code data_generation/scripts/blender_helper.py x: 1 commits (all time) y: 130 lines of code data_generation/scripts/clear_human_scale.py x: 1 commits (all time) y: 110 lines of code data_generation/scripts/extract_pk_data.py x: 1 commits (all time) y: 107 lines of code config/default_cogvideox.py x: 1 commits (all time) y: 58 lines of code config/default_omnimatte.py x: 1 commits (all time) y: 76 lines of code
1386.0
lines of code
  min: 1.0
  average: 217.2
  25th percentile: 79.0
  median: 130.0
  75th percentile: 282.0
  max: 1386.0
0 3.0
commits (all time)
min: 1.0 | average: 1.12 | 25th percentile: 1.0 | median: 1.0 | 75th percentile: 1.0 | max: 3.0

File Size vs. Contributors (all time): 25 points

notebook.ipynb x: 1 contributors (all time) y: 339 lines of code inference/cogvideox_fun/inference_with_pass1_warped_noise.py x: 1 contributors (all time) y: 298 lines of code inference/cogvideox_fun/make_warped_noise.py x: 1 contributors (all time) y: 36 lines of code inference/cogvideox_fun/predict_v2v.py x: 1 contributors (all time) y: 266 lines of code data_generation/render_paired_videos_blender_quadmask.py x: 1 contributors (all time) y: 1386 lines of code data_generation/human_model/human_model.py x: 1 contributors (all time) y: 210 lines of code data_generation/human_model/__init__.py x: 1 contributors (all time) y: 1 lines of code data_generation/apply_physics_config.py x: 1 contributors (all time) y: 49 lines of code data_generation/blender_utils.py x: 1 contributors (all time) y: 374 lines of code data_generation/convert_all_scenarios_for_characters.py x: 1 contributors (all time) y: 145 lines of code data_generation/convert_masks_to_grid_hybrid.py x: 1 contributors (all time) y: 213 lines of code data_generation/convert_trimask_to_quadmask.py x: 1 contributors (all time) y: 166 lines of code data_generation/generate_physics_config.py x: 1 contributors (all time) y: 82 lines of code data_generation/generate_review_frames.py x: 1 contributors (all time) y: 103 lines of code data_generation/generate_review_frames_direct.py x: 1 contributors (all time) y: 123 lines of code data_generation/kubric_variable_objects.py x: 1 contributors (all time) y: 477 lines of code data_generation/object_texture_mapping.py x: 1 contributors (all time) y: 316 lines of code data_generation/physics_review_ui.py x: 1 contributors (all time) y: 180 lines of code data_generation/scripts/blender_helper.py x: 1 contributors (all time) y: 130 lines of code data_generation/scripts/clear_human_scale.py x: 1 contributors (all time) y: 110 lines of code data_generation/scripts/extract_pk_data.py x: 1 contributors (all time) y: 107 lines of code config/default_cogvideox.py x: 1 contributors (all time) y: 58 lines of code config/default_omnimatte.py x: 1 contributors (all time) y: 76 lines of code
1386.0
lines of code
  min: 1.0
  average: 217.2
  25th percentile: 79.0
  median: 130.0
  75th percentile: 282.0
  max: 1386.0
0 1.0
contributors (all time)
min: 1.0 | average: 1.0 | 25th percentile: 1.0 | median: 1.0 | 75th percentile: 1.0 | max: 1.0

File Size vs. Commits (30 days): 0 points

No data for "commits (30d)" vs. "lines of code".

File Size vs. Contributors (30 days): 0 points

No data for "contributors (30d)" vs. "lines of code".

File Size vs. Commits (90 days): 0 points

No data for "commits (90d)" vs. "lines of code".

File Size vs. Contributors (90 days): 0 points

No data for "contributors (90d)" vs. "lines of code".

About This Analysis
  • File size measurements show the distribution of size of files.
  • Files are classified in four categories based on their size (lines of code): 1-100 (very small files), 101-200 (small files), 201-500 (medium size files), 501-1000 (long files), 1001+(very long files).
  • It is a good practice to keep files small. Long files may become "bloaters", code that have increased to such gargantuan proportions that they are hard to work with.
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